随机指标失败摆动策略
该策略监控随机振荡指标,当80以上出现更低的高点或20以下出现更高的低点时留意反转。 指标未能刷新极值并掉头,通常意味着趋势即将变化。 在20下方形成更高低点且%K重新上穿%D时买入;在80上方形成更低高点且%K跌破%D时卖出。 采用小幅百分比止损,若随机指标回到先前摆动水平则退出。
测试表明年均收益约为 70%,该策略在股票市场表现最佳。
细节
- 入场条件:指标信号
- 多/空:均可
- 退出条件:止损或反向信号
- 止损:是,按百分比
- 默认值:
CandleType= 15分钟KPeriod= 14DPeriod= 3OversoldLevel= 20OverboughtLevel= 80StopLossPercent= 2
- 过滤器:
- 类别:反转
- 方向:双向
- 指标:随机指标
- 止损:有
- 复杂度:中等
- 时间框架:日内
- 季节性:否
- 神经网络:否
- 背离:否
- 风险等级:中等
using System;
using System.Collections.Generic;
using Ecng.Common;
using StockSharp.Algo.Indicators;
using StockSharp.Algo.Strategies;
using StockSharp.BusinessEntities;
using StockSharp.Messages;
namespace StockSharp.Samples.Strategies;
/// <summary>
/// K Failure Swing strategy.
/// A trough of %K below OversoldLevel that is higher than the previous such trough arms a long, which opens when %K then crosses
/// above %D; peaks above OverboughtLevel arm shorts the same way. A position closes when %K crosses back through the swing that armed it,
/// and a percent stop limits the loss.
/// </summary>
public class StochasticFailureSwingStrategy : Strategy
{
private readonly StrategyParam<int> _kPeriod;
private readonly StrategyParam<int> _dPeriod;
private readonly StrategyParam<decimal> _oversoldLevel;
private readonly StrategyParam<decimal> _overboughtLevel;
private readonly StrategyParam<decimal> _stopLossPercent;
private readonly StrategyParam<DataType> _candleType;
// The last two values, the last trough and peak in the extreme zones, and the swings that arm an entry.
private decimal? _last;
private decimal? _beforeLast;
private decimal? _lastTrough;
private decimal? _lastPeak;
private decimal? _armedLong;
private decimal? _armedShort;
private decimal _exitLevel;
private decimal? _prevK;
private decimal? _prevD;
/// <summary>
/// Period for %K.
/// </summary>
public int KPeriod
{
get => _kPeriod.Value;
set => _kPeriod.Value = value;
}
/// <summary>
/// Period for %D.
/// </summary>
public int DPeriod
{
get => _dPeriod.Value;
set => _dPeriod.Value = value;
}
/// <summary>
/// %K level below which troughs count.
/// </summary>
public decimal OversoldLevel
{
get => _oversoldLevel.Value;
set => _oversoldLevel.Value = value;
}
/// <summary>
/// %K level above which peaks count.
/// </summary>
public decimal OverboughtLevel
{
get => _overboughtLevel.Value;
set => _overboughtLevel.Value = value;
}
/// <summary>
/// Stop-loss percentage.
/// </summary>
public decimal StopLossPercent
{
get => _stopLossPercent.Value;
set => _stopLossPercent.Value = value;
}
/// <summary>
/// Candle type.
/// </summary>
public DataType CandleType
{
get => _candleType.Value;
set => _candleType.Value = value;
}
/// <summary>
/// Constructor.
/// </summary>
public StochasticFailureSwingStrategy()
{
_kPeriod = Param(nameof(KPeriod), 14)
.SetGreaterThanZero()
.SetDisplay("K Period", "Period for %K", "Indicators");
_dPeriod = Param(nameof(DPeriod), 3)
.SetGreaterThanZero()
.SetDisplay("D Period", "Period for %D", "Indicators");
_oversoldLevel = Param(nameof(OversoldLevel), 20m)
.SetDisplay("Oversold Level", "%K level below which troughs count", "Levels");
_overboughtLevel = Param(nameof(OverboughtLevel), 80m)
.SetDisplay("Overbought Level", "%K level above which peaks count", "Levels");
_stopLossPercent = Param(nameof(StopLossPercent), 2m)
.SetNotNegative()
.SetDisplay("Stop Loss %", "Stop loss percentage from entry price", "Risk");
_candleType = Param(nameof(CandleType), TimeSpan.FromMinutes(15).TimeFrame())
.SetDisplay("Candle Type", "Type of candles to use", "General");
}
/// <inheritdoc />
public override IEnumerable<(Security sec, DataType dt)> GetWorkingSecurities()
{
return [(Security, CandleType)];
}
/// <inheritdoc />
protected override void OnReseted()
{
base.OnReseted();
ResetState();
}
private void ResetState()
{
_last = null;
_beforeLast = null;
_lastTrough = null;
_lastPeak = null;
_armedLong = null;
_armedShort = null;
_exitLevel = default;
_prevK = null;
_prevD = null;
}
/// <inheritdoc />
protected override void OnStarted2(DateTime time)
{
base.OnStarted2(time);
ResetState();
var oscillator = new StochasticOscillator
{
K = { Length = KPeriod },
D = { Length = DPeriod },
};
var subscription = SubscribeCandles(CandleType);
subscription
.BindEx(oscillator, ProcessCandle)
.Start();
StartProtection(new Unit(), new Unit(StopLossPercent, UnitTypes.Percent), useMarketOrders: true, isLocalStop: true);
// The stop has to see prices between candles, not only at their close.
foreach (var field in new[] { Level1Fields.BestBidPrice, Level1Fields.BestAskPrice })
{
var quotes = new Subscription(DataType.Level1, Security);
quotes.MarketData.BuildField = field;
SubscribeLevel1(quotes).Bind(ObserveProtectionQuote).Start();
}
var area = CreateChartArea();
if (area != null)
{
DrawCandles(area, subscription);
DrawIndicator(area, oscillator);
DrawOwnTrades(area);
}
}
private void ObserveProtectionQuote(Level1ChangeMessage quote)
{
// The high-level handler activates native protection before this callback, also between signal bars.
}
private void ProcessCandle(ICandleMessage candle, IIndicatorValue value)
{
if (candle.State != CandleStates.Finished || !value.IsFormed || value.IsEmpty || value is not IStochasticOscillatorValue { K: decimal current, D: decimal signal })
return;
if (_last is decimal last)
{
// The previous value is a trough or a peak once the current one turns away from it.
if (_beforeLast is decimal beforeLast)
{
if (last < beforeLast && last < current && last < OversoldLevel)
{
_armedLong = _lastTrough is decimal trough && last > trough ? last : null;
_lastTrough = last;
}
else if (last > beforeLast && last > current && last > OverboughtLevel)
{
_armedShort = _lastPeak is decimal peak && last < peak ? last : null;
_lastPeak = last;
}
}
var longTrigger = _prevK is decimal pk && _prevD is decimal pd && pk <= pd && current > signal;
var shortTrigger = _prevK is decimal pk2 && _prevD is decimal pd2 && pk2 >= pd2 && current < signal;
var armedLong = longTrigger ? _armedLong : null;
var armedShort = shortTrigger ? _armedShort : null;
if (longTrigger)
_armedLong = null;
if (shortTrigger)
_armedShort = null;
if (IsFormedAndOnlineAndAllowTrading())
{
if (Position > 0)
{
if (current < _exitLevel)
SellMarket(Position);
}
else if (Position < 0)
{
if (current > _exitLevel)
BuyMarket(-Position);
}
else if (armedLong is decimal longSwing)
{
BuyMarket(Volume);
_exitLevel = longSwing;
}
else if (armedShort is decimal shortSwing)
{
SellMarket(Volume);
_exitLevel = shortSwing;
}
}
}
_beforeLast = _last;
_last = current;
_prevK = current;
_prevD = signal;
}
}
import clr
clr.AddReference("StockSharp.Messages")
clr.AddReference("StockSharp.Algo")
clr.AddReference("StockSharp.Algo.Indicators")
clr.AddReference("StockSharp.Algo.Strategies")
clr.AddReference("StockSharp.BusinessEntities")
from System import TimeSpan, Decimal
from StockSharp.Messages import DataType, CandleStates, Unit, UnitTypes, Level1Fields
from StockSharp.BusinessEntities import Subscription
from StockSharp.Algo.Indicators import StochasticOscillator
from StockSharp.Algo.Strategies import Strategy
class stochastic_failure_swing_strategy(Strategy):
"""
K Failure Swing strategy.
A trough of %K below OversoldLevel that is higher than the previous such trough arms a long, which opens when %K then crosses
above %D; peaks above OverboughtLevel arm shorts the same way. A position closes when %K crosses back through the swing that armed it,
and a percent stop limits the loss.
"""
def __init__(self):
super(stochastic_failure_swing_strategy, self).__init__()
self._k_period = self.Param("KPeriod", 14).SetGreaterThanZero().SetDisplay("K Period", "Period for %K", "Indicators")
self._d_period = self.Param("DPeriod", 3).SetGreaterThanZero().SetDisplay("D Period", "Period for %D", "Indicators")
self._oversold_level = self.Param("OversoldLevel", 20.0).SetDisplay("Oversold Level", "%K level below which troughs count", "Levels")
self._overbought_level = self.Param("OverboughtLevel", 80.0).SetDisplay("Overbought Level", "%K level above which peaks count", "Levels")
self._stop_loss_percent = self.Param("StopLossPercent", 2.0).SetNotNegative().SetDisplay("Stop Loss %", "Stop loss percentage from entry price", "Risk")
self._candle_type = self.Param("CandleType", DataType.TimeFrame(TimeSpan.FromMinutes(15))).SetDisplay("Candle Type", "Type of candles to use", "General")
self._reset_state()
@property
def candle_type(self):
return self._candle_type.Value
def _reset_state(self):
# The last two values, the last trough and peak in the extreme zones, and the swings that arm an entry.
self._last = None
self._before_last = None
self._last_trough = None
self._last_peak = None
self._armed_long = None
self._armed_short = None
self._exit_level = Decimal(0)
self._prev_k = None
self._prev_d = None
def OnReseted(self):
super(stochastic_failure_swing_strategy, self).OnReseted()
self._reset_state()
def OnStarted2(self, time):
super(stochastic_failure_swing_strategy, self).OnStarted2(time)
self._reset_state()
oscillator = StochasticOscillator()
oscillator.K.Length = self._k_period.Value
oscillator.D.Length = self._d_period.Value
subscription = self.SubscribeCandles(self.candle_type)
subscription.BindEx(oscillator, self._process_candle).Start()
self.StartProtection(Unit(), Unit(Decimal(self._stop_loss_percent.Value), UnitTypes.Percent), useMarketOrders=True, isLocalStop=True)
# The stop has to see prices between candles, not only at their close.
for field in (Level1Fields.BestBidPrice, Level1Fields.BestAskPrice):
quotes = Subscription(DataType.Level1, self.Security)
quotes.MarketData.BuildField = field
self.SubscribeLevel1(quotes).Bind(self._observe_protection_quote).Start()
area = self.CreateChartArea()
if area is not None:
self.DrawCandles(area, subscription)
self.DrawIndicator(area, oscillator)
self.DrawOwnTrades(area)
def _observe_protection_quote(self, quote):
# The high-level handler activates native protection before the callback, including between bars.
pass
def _process_candle(self, candle, value):
if candle.State != CandleStates.Finished or not value.IsFormed or value.IsEmpty or value.K is None or value.D is None:
return
current = value.K
signal = value.D
os_level = Decimal(self._oversold_level.Value)
ob_level = Decimal(self._overbought_level.Value)
last = self._last
if last is not None:
# The previous value is a trough or a peak once the current one turns away from it.
before_last = self._before_last
if before_last is not None:
if last < before_last and last < current and last < os_level:
self._armed_long = last if self._last_trough is not None and last > self._last_trough else None
self._last_trough = last
elif last > before_last and last > current and last > ob_level:
self._armed_short = last if self._last_peak is not None and last < self._last_peak else None
self._last_peak = last
long_trigger = self._prev_k is not None and self._prev_d is not None and self._prev_k <= self._prev_d and current > signal
short_trigger = self._prev_k is not None and self._prev_d is not None and self._prev_k >= self._prev_d and current < signal
armed_long = self._armed_long if long_trigger else None
armed_short = self._armed_short if short_trigger else None
if long_trigger:
self._armed_long = None
if short_trigger:
self._armed_short = None
if self.IsFormedAndOnlineAndAllowTrading():
if self.Position > 0:
if current < self._exit_level:
self.SellMarket(self.Position)
elif self.Position < 0:
if current > self._exit_level:
self.BuyMarket(-self.Position)
elif armed_long is not None:
self.BuyMarket(self.Volume)
self._exit_level = armed_long
elif armed_short is not None:
self.SellMarket(self.Volume)
self._exit_level = armed_short
self._before_last = self._last
self._last = current
self._prev_k = current
self._prev_d = signal
def CreateClone(self):
return stochastic_failure_swing_strategy()